Big Data in Manufacturing

Several organizations are witnessing the benefits of big data in completing projects to see practical results and significant value. Organizations use big data analytics solutions to make critical and informed business decisions right from new revenue generation and market development to enhancing enterprise-wide performance.

The manufacturing industry is not untouched and leveraging a complete suite of big data and big data technologies to transform business results. Big Data, with its four “V” components – volume, velocity, variety, and varsity – is becoming highly popular.

A comprehensive evaluation of data from different sources – production equipment and systems as well as an enterprise- and customer-management systems – are supporting real-time decision making. In this highly competitive world, analyzing big data use cases in the manufacturing industry can reduce production flaws, maintain high standards of production quality, increase efficiency, and save resources both time and money.

  • Analyze the behavior of customers and understand how goods are delivered in a timely and profitable manner.
  • Big data for predictive analytics aims to significantly decrease the number of tests essential to maintain quality parameters.
  • Calculate the different probabilities of delays and use analytics to identify backup suppliers and develop contingency plans.
  • Quick identification of defects in the manufacturing/production processes

The process requires the mobilization of data from across the enterprise; decipher the intricacies of data to deeply understand its value and determine what data is essential and what data is not. To identify the relevance of data, it is critical to adhere to guidelines.

Infographic Big Data in Manufacturing

Copy the code to include this detailed Infographic of “Big Data in Manufacturing: Challenges, Solutions and Use Cases” on your blog or page:

<img class="size-full wp-image-5984 aligncenter" src="" alt="Big Data in Manufacturing: Challenges, Solutions and Use Cases" width="908" height="4338" />

written by for Big Data Services, Infographics section(s).